Recurrent networks of coupled Winner-Take-All oscillators for solving constraint satisfaction problems

NeurIPS 2013 Hesham MostafaLorenz. K. MuellerGiacomo Indiveri

We present a recurrent neuronal network, modeled as a continuous-time dynamical system, that can solve constraint satisfaction problems. Discrete variables are represented by coupled Winner-Take-All (WTA) networks, and their values are encoded in localized patterns of oscillations that are learned by the recurrent weights in these networks... (read more)

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